title: 3D CT spine data segmentation and analysis of vertebrae bone lesions.
abstract: A method is presented aiming at detecting and classifying bone lesions in 3D CT data of human spine, via Bayesian approach utilizing Markov random fields. A developed algorithm for necessary segmentation of individual possibly heavily distorted vertebrae based on 3D intensity modeling of vertebra types is presented as well.
authors.forename: R
authors.initials: R
authors.lastname: Peter
authors.forename: M
authors.initials: M
authors.lastname: Malinsky
authors.forename: P
authors.initials: P
authors.lastname: Ourednicek
authors.forename: J
authors.initials: J
authors.lastname: Jan
mesh_terms: D000368:Aged; D000465:Algorithms; D001499:Bayes Theorem; D001859:Bone Neoplasms / Q000000981:diagnostic imaging* / Q000556:secondary; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional; D008297:Male; D008390:Markov Chains; D008875:Middle Aged; D011857:Radiographic Image Interpretation, Computer-Assisted; D013131:Spine / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed / Q000379:methods